File size: 4,786 Bytes
5289fea | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | #!/usr/bin/env bash
# ─────────────────────────────────────────────────────────────────────────────
# OpenJev zero-GPU entrypoint (Docker Space).
# 1. Download the chosen GGUF once into /data (HF persistent storage) — the
# 16.2 GB load survives restarts/sleeps, so wake-ups are fast.
# 2. Fetch the OpenJev tokenizer (needs tokenizer.json + chat template).
# 3. Start llama.cpp `llama-server` on CPU with logprobs enabled.
# 4. Start the OFFICIAL openjev-server, its `vllm` backend pointed at the
# llama.cpp OpenAI endpoint (top-logprobs fallback path, no code changes).
# openjev-server binds $OPENJEV_PORT (7860) - the HF Spaces ingress.
# ─────────────────────────────────────────────────────────────────────────────
set -euo pipefail
log() { printf '\n\033[1;34m[entrypoint]\033[0m %s\n' "$*"; }
# config
MODEL_REPO="${MODEL_REPO:-openjev/openjev-GGUF}"
MODEL_FILE="${MODEL_FILE:-OpenJev-Q4_K_M.gguf}"
TOKENIZER_REPO="${TOKENIZER_REPO:-openjev/openjev}"
LLAMA_PORT="${LLAMA_PORT:-8080}"
OPENJEV_PORT="${OPENJEV_PORT:-7860}"
LLAMA_CTX="${LLAMA_CTX:-8192}"
LLAMA_MAX_LOGPROBS="${LLAMA_MAX_LOGPROBS:-64}"
LLAMA_PARALLEL="${LLAMA_PARALLEL:-1}"
LLAMA_THREADS="${LLAMA_THREADS:-}"
LLAMA_THREADS_BATCH="${LLAMA_THREADS_BATCH:-}"
MODEL_DIR="${MODEL_DIR:-/data/models}"
MODEL_PATH="${MODEL_DIR}/${MODEL_FILE}"
TOKENIZER_DIR="${TOKENIZER_DIR:-/data/tokenizer}"
mkdir -p "$MODEL_DIR" "$TOKENIZER_DIR"
# ── 1. model (one-time download; persists in /data across restarts) ─────────
if [ ! -s "$MODEL_PATH" ]; then
log "downloading $MODEL_REPO/$MODEL_FILE -> $MODEL_DIR (one-time, ~16 GB, persistent)"
HF_HUB_ENABLE_HF_TRANSFER="${HF_HUB_ENABLE_HF_TRANSFER:-1}" python - <<'PY'
import os
from huggingface_hub import hf_hub_download
repo, fname, d = os.environ["MODEL_REPO"], os.environ["MODEL_FILE"], os.environ["MODEL_DIR"]
print("hf_hub_download:", repo, fname)
p = hf_hub_download(repo_id=repo, filename=fname, local_dir=d, resume_download=True)
print("downloaded to", p)
PY
else
log "model already on disk: $MODEL_PATH ($(du -h "$MODEL_PATH" | cut -f1))"
fi
# ── 2. tokenizer snapshot (openjev-server needs tokenizer.json + chat template)
if [ ! -e "$TOKENIZER_DIR/tokenizer.json" ]; then
log "fetching tokenizer from $TOKENIZER_REPO"
python - <<'PY'
import os
from huggingface_hub import snapshot_download
print(snapshot_download(repo_id=os.environ["TOKENIZER_REPO"], local_dir=os.environ["TOKENIZER_DIR"],
allow_patterns=["tokenizer*", "vocab*", "merges*", "*.json", "config*", "special_tokens_map*", "*.jinja"]))
PY
else
log "tokenizer already present in $TOKENIZER_DIR"
fi
# ── 3. llama.cpp server (CPU) ───────────────────────────────────────────────
LLAMA_ARGS=(
--host 127.0.0.1 --port "$LLAMA_PORT"
--model "$MODEL_PATH"
--ctx-size "$LLAMA_CTX"
--n-predict 1
--parallel "$LLAMA_PARALLEL"
--logprobs "$LLAMA_MAX_LOGPROBS"
--alias openjev
--log-file /tmp/llama-server.log
--no-warmup
)
[ -n "$LLAMA_THREADS" ] && LLAMA_ARGS+=(--threads "$LLAMA_THREADS")
[ -n "$LLAMA_THREADS_BATCH" ] && LLAMA_ARGS+=(--threads-batch "$LLAMA_THREADS_BATCH")
log "starting llama-server (CPU) on 127.0.0.1:$LLAMA_PORT"
llama-server "${LLAMA_ARGS[@]}" &
LLAMA_PID=$!
# wait until llama.cpp accepts requests (up to 15 min on a cold boot)
python - <<'PY'
import os, sys, time, urllib.request
url = f"http://127.0.0.1:{os.environ['LLAMA_PORT']}/v1/models"
for _ in range(450):
try:
with urllib.request.urlopen(url, timeout=10) as r:
if r.status == 200:
print("llama-server is ready"); sys.exit(0)
except Exception:
pass
time.sleep(2)
print("llama-server did not become ready in time"); sys.exit(1)
PY
# ── 4. official openjev-server (vllm backend -> llama.cpp fallback path) ────
export OPENJEV_BACKEND=vllm \
OPENJEV_VLLM_URL="http://127.0.0.1:${LLAMA_PORT}/v1" \
OPENJEV_MODEL="$TOKENIZER_DIR" \
OPENJEV_SERVED_MODEL_NAME="${OPENJEV_SERVED_MODEL_NAME:-openjev}" \
OPENJEV_HOST=0.0.0.0 \
OPENJEV_PORT="$OPENJEV_PORT" \
OPENJEV_PROFILE="${OPENJEV_PROFILE:-openjev}"
cleanup() { kill "$LLAMA_PID" 2>/dev/null || true; }
trap cleanup EXIT INT TERM
log "openjev-server listening on 0.0.0.0:$OPENJEV_PORT (UI + /v1/systemone + /docs + /healthz)"
exec openjev serve --force |